Target-based augmented-reality (AR) devices allow users to view information linked to image targets identified by the devices in real time. One type of AR devices is a see-through head mounted display (HMD). A see-through HMD is a display device, worn on the head or as part of a helmet, in which computer generated images are projected on a partially reflective mirror to afford users a simultaneous real-world view. For example, a camera-enabled HMD worn by a shopper may identify image targets of products in the field of view of the shopper and may display to the shopper information on those products. Similarly, a body mounted camera worn by a user may track targets in the vicinity of the user and may display AR information on the targets to a smartphone linked to the camera for viewing by the user.
Conventionally, target-based AR is an active experience requiring participation from the users to identify image targets. For example, a user running an AR application on a target-based AR device typically points a camera at a target and activates the camera to scan the target. An image or fingerprint of the target is taken and compared against a device-based target database or a cloud-based target database for target identification. If there is a match, the target-based AR device retrieves AR content linked with the identified image target and renders the AR content on the screen of the AR device. One drawback of user-activated target identification is that unless AR image targets are clearly labeled as such, users do not know if the targets have AR content. In fact, the user is generally aware that the likelihood of any random target such as a random magazine cover, photo, poster, logo, or print advertisement having AR content linked to it is very small. Therefore, users may be discouraged from activating cameras to scan potential image targets.
Conversely, labeling AR image targets as such defeats the purpose of target-based AR because image labeling of targets then becomes another form of image-to-content linking such as QR codes. One way to free users from the need to activate image target identification is for camera-enabled HMDs or other user-worn camera systems to autonomously, continuously scan targets for identification of AR image targets. However, the power requirement for running the camera, communicating the image targets, and identifying the image targets on a continuous basis makes this solution unfeasible for HMDs and user-worn cameras with limited battery capacity. As such, there is a need for target-based AR devices to provide autonomous, low-power AR image target scanning and identification.